The improvement of Unmanned Aerial System (UAS) and photogrammetric computer vision (CV) algorithms have presented an aerial imaging technique for high accuracy and low-cost alternatives for mapping and topographic applications. Structure from motion (SFM) is an automation photogrammetric CV algorithm used for generating 3D colored point clouds and 3D models from overlapping images. One of the biggest problems preventing the automation extraction and matching key points in the aligning aerial images is the featureless surface of the covered area. This paper assessed the effect of flight altitude and overlap ratio on 3D point clouds' geometric accuracy and models produced by Unmanned Aerial Vehicle (UAV) images captured over non-textured sandy areas. Four different flight altitudes (140 m, 160 m, 180 m, and 200m) related to spatial resolution (3.41, 3.9, 4.39, 4.68 cm/pix GSD), respectively and three different overlap levels (60 %, 70 %, and 80 %) were assessed using RGB images captured by UX5 UAV over a non-textured sandy area in Jahra, Kuwait. The results showed that altitude increment might reduce flight time, processing time, and cost with keeping the acceptable and suitable geometric accuracy. The different UAV altitudes 140, 160, 180, and 200 m AGL gave geometric accuracy 0.043, 0.049, 0.052, and 0.057 m for IG process and 0.036, 0.039, 0.048, and 0.053 m for DG process, respectively. The increasing of image overlap ratio from 60 % to 80 % leads to an increase in photogrammetric point clouds' geometric accuracy from 0.685m to 0.049 m for IG process. Generally, favorable results are obtained for the four different altitudes and overlap ratios of 80 % at least.